Wellcome Open Research

Autosomal dominant polycystic liver disease (ADPLD) commonly results from a pathogenic variant in one of 6 genes (GANAB, ALG8, LRP5, PRKCSH, SEC61B, SEC63). Pathogenic variants in these genes are also associated with kidney cysts, which rarely cause kidney failure, but the genes are included in cystic kidney panels. This study determined the population frequency of predicted pathogenic variants in the ADPLD genes in the general population. Variants for each gene were downloaded from gnomAD and annotated with ANNOVAR. The population frequencies were calculated from the number of people with "predicted pathogenic" variants in gnomAD v.2.1.1:loss-of-function structural and copy number; null; and rare, computationally-damaging missense changes that affected a conserved residue. Frequencies were also estimated from the number of gnomADv.4.1 variants assessed as Pathogenic or Likely pathogenic in ClinVar. Predicted pathogenic variants affected one in 95 people using our strategy and gnomAD v.2.1.1, and one in 151 with ClinVar assessments of gnomAD v.4.1 variants. LRP5 and ALG8 which are associated with a milder clinical phenotype, were the commonest affected genes with both strategies. Predicted pathogenic variants in ADPLD appear more frequent in admixed American (one in 100), Finnish (one in 107) and African/African American (one in 130) people (p all <0.0001 compared with Europeans (one in 197).Predicted pathogenic variants for ADPLD may be even more common because of additional unidentified causative genes. However not all ADPLD variants result in liver cysts, nor indeed cystic kidneys, because of incomplete penetrance and variable expressivity.

Background and hypothesis Autosomal dominant polycystic kidney disease (ADPKD) affects over 12 million people worldwide including an estimated 30,000-70,000 in the United Kingdom (UK). Tolvaptan is the only disease-modifying therapy approved for rapidly progressing disease. Despite national guidance, prescribing rates were hypothesised to vary by kidney centre. Treatment may not always align with guidelines: some patients eligible for tolvaptan may not be initiated, while other patients initiated on tolvaptan may not meet eligibility criteria. This may have important consequences for healthcare costs and health-related quality of life. Methods The National Registry of Rare Kidney Diseases (RaDaR) collects longitudinal data from UK NHS kidney centres. This retrospective cohort study used routinely collected data (2016-2023) to examine tolvaptan prescribing across kidney centres. Kidney centre-level initiation patterns were described, assessed using mixed-effects logistic regression and visualised with funnel plots. Cost-effectiveness analyses combined observed prescribing practices under likely negotiated commercial discounts to estimate costs and quality-adjusted life year (QALY) consequences of prescribing at the national level. Results Our study included 3,609 people with ADPKD from 72 kidney centres. Patients eligible for tolvaptan who were not initiated accounted for 34.8% (292/839). Across centres, five (6.9%) initiated tolvaptan significantly more than expected among eligible participants, while one centre (1.4%) initiated significantly less. Nationally, this could result in up to {pound}53.7 million in lost savings (assuming a 60% medication price reduction) and result in up to 1,245 lost QALYs. Patients initiated on tolvaptan who were not eligible accounted for 26.1% (103/395). Only one centre had significantly fewer eligible patients than expected among initiated patients. Nationally, this could cost up to {pound}15.9 million (assuming a 60% medication price reduction). Conclusions There is evidence of variation in tolvaptan prescribing in the UK. A substantial proportion of patients eligible for tolvaptan were not initiated at the cohort-level, with evidence of variation between centres suggesting differences in treatment decision-making. A substantial proportion of patients initiated on tolvaptan were not eligible at the cohort-level, but there was limited evidence of variation between centres. Together, these findings raise questions regarding the potential consistency of clinical decision-making, equitable access to a sole disease-modifying therapy in a rare disease, alignment with national guidance, and effective use of healthcare resources.

Background Social contact surveys, which measure who-contacts-whom, are widely used to inform infectious disease transmission models and estimate the reproduction number (R), a key metric for assessing epidemic risk. Despite their widespread use, sample size calculations are not routinely performed. Aims To assess the impact of sample size on estimates of R and determine a practical target sample size for social contact surveys used in epidemic modelling. Methods We conducted a review of social contact surveys (2008-2025) to characterise current practice. We characterised the impact of survey size on epidemic metrics using two social contact surveys, the UK Social Contact Survey and POLYMOD (Europe) and two methods. For each dataset and approach, we generated repeated subsamples and calculated the resulting reproduction numbers, characterised their distributions and measured uncertainty. Results We identified 107 unique social contact surveys from 57 studies. Sample sizes ranged from 30 to more than 10,000 participants, with a median of 1,438. One quarter of surveys contained fewer than 1,000 participants. From our simulations, we find that sample sizes below 200 individuals can result in highly variability reproduction numbers. Increasing sample size increases precision, and the most meaningful gains are up to 1,300 individuals. Increasing sample sizes over 3,000 individuals leads to smaller gains. Conclusions A minimum sample size of approximately 1,200-1,300 participants appears sufficient for general-purpose use. These findings support the inclusion of sample size considerations in the design, reporting and interpretation of social contact surveys used for epidemic intelligence and public health decision-making.

Here we evaluated the performance of a previously published tiling PCR primer scheme by Ringlander et al. (2022) for whole-genome amplification of Hepatitis B virus (HBV) in combination with Oxford Nanopore sequencing. The primer set originally developed for Ion Torrent sequencing was adapted by removing platform-specific adapters and tested using clinical serum or plasma samples submitted for routine HBV genotyping and resistance testing. Two multiplexing strategies were compared: a single PCR pool containing all primers and a two-pool strategy with non-overlapping amplicons. Sequencing reads were processed using a Nanopore analysis pipeline, and genome coverage and amplicon performance were compared across samples spanning a wide Ct range and representing HBV genotypes A-E. Across all samples, the median genome coverage was approximately 50%, although recovery varied widely, ranging from complete failure to nearly full genomes. Combining all primers into a single PCR reaction, or separating overlapping amplicons into different reactions, had little overall impact on genome recovery, and no consistent differences between the two pooling strategies were observed. In contrast, amplification efficiency differed markedly between individual amplicons. Amplicons 1-5 generally produced higher sequencing depth, whereas amplicons 6-10 frequently showed low coverage and contributed to incomplete genome recovery. Genome coverage was strongly associated with Ct values, with higher coverage observed in samples with lower Ct values, while coverage was broadly similar across genotypes. These results demonstrate that the Ringlander et al. primer scheme can be adapted for multiplex PCR and Nanopore sequencing of HBV, but uneven amplicon performance limits consistent full-genome recovery and highlights the need for further optimization of HBV tiling PCR designs.

BackgroundHumans and mice display elevated levels of IL-27, an immunosuppressive cytokine shown to increase during neonatal bacterial sepsis and compromise survival. This study explores two hypotheses for regulation of IL-27 expression: 1) decreased DNA methylation in newborns that contributes to increased expression of IL-27 genes; 2) neonatal hormones regulate IL-27 expression through upstream hormone response elements (HREs). MethodsWhole genome methyl-seq analysis of neonatal and adult blood-derived macrophages identified differentially methylated regions (DMRs) at steady-state. Quantitative PCR (qPCR) measured expression of IL-27 genes (IL27p28 and EBI3) in human and murine neonatal macrophages stimulated in vitro with synthetic glucocorticoid or progesterone. Confocal microscopy and chromatin immunoprecipitation (ChIP) of glucocorticoid receptor (GR) assessed translocation into the nucleus and binding to the EBI3 promoter. ResultsThe IL-27p28 promoter contained DMRs that were increased in the neonatal cohort. The analysis did not identify DMRs within the EBI3 promoter. Dexamethasone stimulation increased EBI3 gene expression in human and murine neonatal macrophages. GR localized to the nucleus in response to dexamethasone and was enriched at the EBI3 upstream regulatory region. ConclusionThese data suggest glucocorticoid (GC) signaling increases EBI3 expression. This has importance in the context of antenatal GC administration that may increase IL-27 levels. Impact Statement{blacksquare} Elevated expression of IL-27 in early life impairs the host response to invasive bacterial infection in neonates. {blacksquare}Understanding the regulatory mechanisms contributing to increased IL-27 during the neonatal period is necessary to reduce susceptibility to infection in this vulnerable population. {blacksquare}The methylation status of the IL-27 genes in macrophages from neonatal and adult blood donors does not suggest regulation of differential expression with age. {blacksquare}Glucocorticoids are a signal that can induce EBI3 gene expression in a GR-dependent manner. {blacksquare}Glucocorticoid therapy for premature infants may increase IL-27 expression and promote enhanced susceptibility to infection.

BackgroundMetabolic dysfunction-associated steatotic liver disease (MASLD) is challenging to study in vivo in humans and in vitro models are limited. Although primary human hepatocytes (PHHs) are considered the gold-standard, immortalized hepatic cell lines are utilised due to scalability. This study compared the metabolic responses of PHHs with our Huh7-based model cultured in physiologically-relevant fatty acid (FA) mixtures. MethodsPHH and Huh7 cells were treated with 2% human serum, sugars and FAs enriched in either unsaturated (OPLA) or saturated (POLA) FAs for 4 or 7 days, respectively. Stable isotope tracers investigated basal metabolic changes in response to treatment. Cell viability, media biochemistry, intracellular metabolism, lipid droplet morphology and gene expression were quantified. ResultsHuh7 cells had greater viability than PHHs, while NEFA uptake and triglyceride secretion were similar. OPLA and POLA increased large lipid droplets in Huh7 cells, whereas only OPLA produced comparable effects in PHHs. Despite higher baseline TG in PHHs, both models showed similar lipid composition, de novo lipogenic responses, and glycogen levels. Compared to Huh7 cells, PHHs exhibited higher 3-hydroxybutyrate, lower lactate, reduced glucose uptake, and donor-dependent transcriptomic variability. ConclusionsHuh7 cells are metabolically adaptable and when cultured in physiologically-relevant media, produce metabolic readouts similar PHH cells.

Summary (Abstract)An increasing number of research institutions and funding bodies are making sustainability a focal point in research funding and practice. Across the UK, the rapid rollout of auditing processes, such as the Laboratory Efficiency Assessment Framework (LEAF) and changing institutional policies, are creating pressing, focal demand for sustainability accounting upon UK researchers. Despite the increasing expectations on UK researchers to actively report their sustainability and demonstrate improvement, easy-to-use, and accurate reporting tools for sustainability accounting are not widely available. Here, we created WillCO2st - a free program that enables fast, publication-read sustainability reports. WillCO2st makes use of real-time, region-specific conversion factor data freely available through the Carbon Intensity API - a resource unique to the UK - to create experimental carbon footprinting estimates using metadata of experimental files. Data can be simply click-and-dragged into WillCO2st to create an experimental sustainability audit in minutes. Further, we exemplified the utility of WillCO2sts live-nudging feature by quantifying the retrospective theoretical savings in carbon from shifting experimental timing to times of day with lower carbon intensities. Overall, WillCO2st eases time and resource burden on researchers and serves as a national model within the UK that could be replicated in other countries as relevant data on regional energy use becomes available. HighlightsO_LIWillCO2st is a free software platform that enables fast, publication-ready sustainability reporting for papers, grants, and internal audits. C_LIO_LIWillCO2st leverages the Carbon Intensity API to provide real-time, UK region-specific estimations of carbon intensity and nudges users to switch to lower carbon alternative timing of activities. C_LIO_LIPartial conformity (21%) to switching experimental time would have disproportionately produced a large carbon saving (50%) in our most recent publications experimental carbon footprint. C_LI

BackgroundPrimary care practitioners are well-positioned to support people of reproductive age in preparing for pregnancy and parenthood. Such "preconception care" is ideally delivered opportunistically during routine consultations, although limited time presents a barrier. AimTo achieve consensus on priority topics for opportunistic preconception care in general practice. Design and settingA three-step consensus study involving UK-based primary care practitioners and people of reproductive age. MethodThe consensus process involved: 1) identifying potential topics through literature and guideline reviews, workshops with people of reproductive age (n=15), and interviews with primary care practitioners who work in general practice (n=14); 2) prioritising topics using a Delphi survey (n=85 participants completing round one, n=63 completing all three rounds); and 3) agreeing on priority topics during an online consensus workshop (n=21 participants). Participants were recruited through a Public Advisory Group, charities, and professional organisations. ResultsReviews and workshops/interviews with people of reproductive age and practitioners identified 37 potential topics. The Delphi survey and consensus workshop identified 16 priority topics. These were combined into four overarching topic areas for discussion during relevant consultations: O_LIPatient knowledge of preconception health and pregnancy C_LIO_LIIdeas, concerns and expectations (e.g. pregnancy intention, prior pregnancy experiences) C_LIO_LIHealth conditions (e.g. medication use, mental/physical health, immunisation) C_LIO_LIHealth behaviours (e.g. folic acid supplement use, smoking, alcohol consumption). C_LI ConclusionThe agreed priority topic areas offer a structured foundation for delivering patient-centred, opportunistic preconception care in primary care. The findings support future co-development of practical tools and resources to enable routine implementation. How this fits inPreconception care improves pregnancy outcomes, but in UK general practice it is inconsistently delivered, partly due to limited time and guidance that offers little prioritisation for opportunistic consultations. This study identifies four overarching topic areas for preconception care, based on consensus among people of reproductive age and primary care practitioners. The resulting priority list offers clinicians a practical, flexible way to initiate patient-centred preconception care discussions within routine consultations.

IntroductionInternational goals aim to eliminate Hepatitis B Virus (HBV) as a public health threat by 2030, but data representing African populations remain limited. We therefore investigated the population prevalence of HBV and treatment eligibility in a rural South African setting. MethodsWe tested archived plasma samples from 2200 participants in a population-based study in KwaZuku Natal for HBV surface antigen (HBsAg), HBV core antibody (anti-HBc), and HBV surface antibody (anti-HBs). For samples testing HBsAg-positive, we quantified alanine transferase (ALT) and HBV DNA viral load. We evaluated demographic and clinical correlates of HBV biomarkers, explored the geographical distribution of HBsAg, and assessed HBV treatment eligibility. ResultsWeighted HBV infection prevalence was 10.4% (95% CI: 9.0%-12.1%). Evidence of HBV exposure and clearance was found in 34.9% (95% CI: 32.4 - 37.5). Overall prevalence of vaccine-mediated HBV immunity was 8.9% (95% CI: 7.5%-10.4%) but for the sub-group born between 2000-2005 (after the HBV vaccine was implemented) this increased to 20.2% (95% CI 15.8-25.4). Infection prevalence was highest in the South of the region. Over 60% of individuals testing HBsAg-positive met treatment eligibility criteria. ConclusionPrevalence of HBV infection and exposure in this setting is high, while vaccine-mediated immunity is low. These data highlight a pressing need for scale-up of interventions to support progress towards global elimination targets. FundingThe Francis Crick Institute (ref. CC2223), the Africa Oxford Initiative (Research Development Award) and Wellcome Strategic Core Award (227167/A/23/z). EthicsUniversity of KZN (UKZN) ref. 00004495/2022; University College London ref. 23221/001.

Health research priorities are generally not aligned with global disease burden. Although genome-wide association studies (GWAS) are correcting a historical bias by including samples from different demographic groups, this does not necessarily translate to improved understanding of the most important causes of disease globally. We demonstrate that while in countries with high socioeconomic development index (SDI) there is some alignment between the traits being analysed in GWAS and those that contribute most to disease burden, there is almost no such alignment in countries with low SDI. Improvement in alignment between GWAS and disease burden has been seen for countries with middle SDI over time, likely due to the contributions to disease burden changing in those regions rather than GWAS responding to the needs of those regions. Low GWAS alignment with disease burden may be partially explained by lower GWAS attention to childhood health. Improving aetiological understanding of high burden neglected conditions should be a priority for emerging biobanks in order to reduce global health inequality. Short abstractWe identify some alignment between the traits being analysed in genome-wide association studies (GWAS) and disease burden in high socioeconomic development index (SDI) countries, while there is almost no such alignment in countries with low SDI, mostly due to neglecting childhood infection. Improvement in alignment between GWAS and disease burden has been seen for countries with middle SDI over time likely due to changing disease burden.

FluSurvey is a participatory surveillance system used to monitor trends in influenza and other respiratory viruses through weekly symptom surveys among the UK population. We aimed to characterise the wider impact of "influenza-like illnesses" (ILI) among FluSurvey participants and assess correlations of ILI with other established influenza surveillance systems. We included data reported by FluSurvey participants over the 2023-24 and 2024-25 winter seasons. Using weekly symptoms surveys, we derived ILI episodes and estimated the proportion reporting healthcare service use, medication use, impact on daily life, absenteeism and use of tests. We applied existing methodologies (omitting first report and weighting to the age-sex structure of England) and assessed cross-correlations of weekly FluSurvey ILI rates with the national surveillance of GP ILI consultations, influenza hospital admissions, and influenza PCR test positivity at time lags of up to +/- 2 weeks. There were 3057 participants over two winter seasons (N2023-24=2540, 63% female, mean age 60 years; N2024-25=2273, 64% female, mean age 61 years). Of 1868 ILI episodes, only a minority contacted healthcare services (14%, most frequently visiting the GP). A large proportion of episodes reported medication use (89%), impact on daily life (75%) and missing school or work (47%). Notable differences in testing behaviour were apparent by season, with fewer reporting use of tests in 2024-25. FluSurvey ILI rates were strongly correlated with other influenza surveillance, predominantly leading GP ILI consultations (max r=0.73), coinciding with influenza hospital admissions (max r=0.88) and lagging influenza test positivity (max r=0.88). The majority of ILI reported to FluSurvey do not contact healthcare due to symptoms but experienced wider impacts on daily life. FluSurvey ILI corresponds well with other national influenza surveillance and provides broader context on community illness, supplementing the monitoring of influenza activity for public health response.

BackgroundChildren who are HIV-exposed but uninfected (HEU) are at increased risk of neurodevelopmental delays, yet neuroimmune pathways linking perinatal HIV exposure to school readiness remain unclear. MethodsIn the Drakenstein Child Health Study, 268 children (94 HEU, 174 HIV-unexposed [HU]) underwent magnetic resonance spectroscopy in midline parietal grey and left parietal white matter regions at 6-7 years. Peripheral blood serum immune markers were measured in pregnancy and in children at 6 weeks, 2, 3, and 5 years. Linear mixed-effects models characterised child immune trajectories and linear regressions tested associations with creatine-referenced neurometabolite ratios and school readiness scores. ResultsMothers living with HIV had higher sCD14 and lower MMP-9, NGAL, and GM-CSF than mothers without HIV (p<0.05). Perinatal HIV exposure was associated with altered trajectories of child sCD14, GM-CSF, IL-1{beta}, IL-5, IL-10, and YKL-40. At 6-7 years, children who were HEU had lower parietal grey matter glutamate ratios and lower left parietal white matter choline ratios. By school entry, immune-neurometabolite associations were predominantly driven by child serum markers; IL-8 emerged as a consistent correlate across developmental stages. Children who were HEU had lower language scores than HU peers. Left parietal white matter choline ratios were positively associated with language and overall school readiness in HU children, but not HEU. ConclusionsPerinatal HIV exposure was associated with alterations in immune development, neurometabolites reflecting both white matter maturation and neuronal health, and school readiness. Our findings highlight potential neuroimmune pathways contributing to neurodevelopmental risks in children who are HEU.

BackgroundDatasets related to infectious diseases are essential for public health decision-making, yet their reuse remains limited by persistent barriers to data sharing and integration. Achieving data that are Findable, Accessible, Interoperable, and Reusable (FAIR) is widely recognized as essential for accelerating scientific discovery and enabling coordinated responses to emerging threats, but the needs of the global pathogen data community have not been systematically characterized. AimThis study, conducted by the Pathogen Data Network (PDN), aims to identify infrastructural and educational priorities among stakeholders working with infectious disease-related data in order to guide community-responsive support for data sharing and interoperability. MethodsA cross-sectional stakeholder survey was disseminated to a well-defined expert population within PDN networks and via open professional channels. A total of 136 responses from researchers, healthcare professionals, bioinformaticians, and educators were analyzed descriptively to identify prioritized barriers, training needs, and preferred support mechanisms. ResultsRespondents consistently identified structural constraints as the primary impediments to effective data use, including limited funding (74%), data-aggregation challenges (68%), and a shortage of skilled personnel (52%). Respondents identified bioinformatics for infectious disease research (68%) as the highest priority for training, followed by guidance on using the integrated pathogen data and tools portal provided by the PDN, the Pathogens Portal (51%). The Pathogens Portal was also ranked as the most essential PDN resource (72%). Preferred training formats included virtual short courses (68%) and webinars (66%). Notably, while researchers emphasized technical subjects like machine learning, educators prioritized foundational case studies. ConclusionThese findings provide an evidence-based diagnostic of community needs and suggest that barriers to FAIR pathogen data are predominantly systemic rather than purely technological. The survey framework and openly available dataset offer a reusable template for assessing needs in other communities and regions. By aligning training, infrastructure development, and outreach with empirically identified priorities, organizations supporting infectious disease research can strengthen the interoperability and reuse of data and establish a benchmark for future community-driven improvements.

SignificanceSelecting the appropriate motion artefact (MA) correction method for functional near-infrared spectroscopy (fNIRS) data is quite challenging, particularly in light of the need for standardised practice, replication, and transparency in the field. A clear framework for making measurable and replicable decisions is therefore essential. AimThis paper proposes a guide based on an open-source data quality assessment tool (QT-NIRS) that enables a transparent and evidence-driven choice of MA correction method. ApproachWe present the guide in two approaches: a simplified version that is easy to run for beginners, and an advanced version providing more informative output at the cost of additional computations and minor changes to the original QT-NIRS code. Due to its high flexibility and within-subject nature, the method is applicable across samples with varied characteristics. ResultsWe applied the guide to two challenging datasets from 60 British preschoolers (mean age = 3.94 years, SD = 0.49) and 39 South African school children (mean age = 12.00 years, SD = 0.51). Both simplified and advanced approaches supported similar MA correction methods. ConclusionsWhile both approaches can be used interchangeably, we recommend the advanced approach when possible due to its more informative and straightforward output, and advise caution when using the simplified version.

BackgroundEpidemic forecasting research often assesses ensembles and their component models using probabilistic scoring rules. Quantifying how individual models affect ensemble performance is challenging, particularly across multiple targets and spatial scales. MethodsWe present Winter 2024-25 forecasts of Influenza and COVID-19 hospital admissions in England and conduct a retrospective simulation using the operational component models. Forecasts were scored using the per capita weighted interval score (pcWIS) for counts and the ranked probability score (RPS) for ordinal trend direction. We compared operational retrospective forecasts, used generalised additive models (GAMs) to estimate the expected change in score from the inclusion of a model in a sub-ensemble, and used Pareto analysis to understand which sub-ensembles were Pareto-optimal across scoring rules. ResultsNationally, the Influenza and COVID-19 operational ensembles achieved pcWIS of 5.20 x 10-7 and 3.98x 10-7, with RPS of 0.234 and 0.171 respectively. This corresponds to a 47% improvement in score versus sub-ensembles for Influenza pcWIS. However, Influenza operational ensembles were 22% worse than sub-ensembles, on average, when measured by RPS. For COVID-10, operational ensembles were 43% and 265% worse on average, than retrospective sub-ensembles by pcWIS and RPS, respectively. The sub-ensemble simulation showed individual models influenced the ensembles during different epidemic phases. The Pareto analysis demonstrated that there can be a trade-off between relative direction and absolute count score optimisation. InterpretationOur analysis shows that UKHSA forecasts were well calibrated with observations and often had comparable performance to optimal ensembles. Our GAM and Pareto analyses inform model selection for future ensembles. Author SummaryForecasts of winter hospital pressures in England are an important tool for senior healthcare leaders. It is common practice to produce a forecasting ensemble, i.e. combine the predictions of multiple models to create a single, more accurate prediction. Forecasting teams should strive to produce the best forecast possible; one tool for this is retrospective evaluation over a forecasting season using proper scoring rules to assess performance. Our forecasts are constructed of two components, an epidemic trend direction estimate as well as forecast of hospital admission numbers. There are two main challenges we address. The first is understanding at which epidemic phase different ensemble contributions are most effective, the second is the joint optimisation of an ensemble for both trend direction and admission numbers forecast. We apply these methods to a variety of ensembles (sub-ensembles) based on our own modelling suite, and compare the sub-ensembles to our operational forecasts from the Winter 2024/25 season.

BackgroundRespiratory syncytial virus (RSV) is a leading cause of severe acute respiratory infection in infants, young children and vulnerable adults. Despite implications for designing interventions, our understanding of RSV infection/reinfection patterns during community outbreaks is incomplete. MethodsTo characterize respiratory virus infections regardless of symptom status, we performed a prospective cohort surveillance in coastal Kenya from August 2023 to August 2024. Nasopharyngeal/oropharyngeal (NP/OP) swabs were collected 1-2 times weekly regardless of symptom status for quantitative PCR testing followed by genomic analysis. RSV reinfections were defined as two positive tests separated by [&ge;]14 days and with intervening [&ge;]1 negative tests. ResultsOf 672 individuals screened, 74 tested positive (93/22,000 swabs; 0.4%). The median age among infections was 4.2 years (interquartile range (IQR): 1.8-9.4), 58.1% being female versus a median age of 14.3 years (IQR: 4.8-29.6) and 64.4% female among uninfected individuals. Overall incidence rate was 19.8 infections/100 person-years, highest incidence among infants (174.0/100 person-years, 95% CI:103.0-274.0). Infection episodes fell into seven viral lineages: A.D (n=1), A.D.1 (n=2), A.D.1.11 (n=21), A.D.2.1 (n=19), A.D.3 (n=30), A.D.5.2 (n=1), and B.D.E.1 (n=2). Six individuals (8.1%; 13.7/100 person-years) experienced reinfections, three involving same viruses with 0-3 nucleotide differences across the entire RSV genome, while other three had 20,78 and 200 nucleotide differences. The (suspect) reinfected individuals were all under 2 years of age, included both males and females, and had no reported chronic illnesses. ConclusionRSV community infections predominantly occur in children regardless of clinical presentation. Reinfections within the same season are rare. Key pointsO_LIIn a community cohort prospective study in coastal Kenya, RSV-A predominated the 2023/24 epidemic and seven lineages co-circulated. C_LIO_LIOverall incidence was 19.6 infections/100 person-years and highest in infants. C_LIO_LIMost reinfections (5/6) were asymptomatic and only half had amino acid changes. C_LI

Background & AimsAntiviral therapies targeting hepatitis B virus (HBV) suppress viral replication, but rarely achieve functional cure. Understanding HBV-host cell interaction is crucial for developing novel therapeutic approaches. Here, we report host cell proteins associated with HBV virions and filamentous subviral particles (fSVPs) and characterize one of them, apolipoprotein C1 (ApoC1), mechanistically. MethodsHighly purified HBV virions and fSVPs were obtained by sequential use of several biophysical methods. Particles were analyzed by mass spectrometry and associated proteins were evaluated phenotypically using an HBV infection model. The top hit, ApoC1 was characterized in detail. ResultsAssociated with virions and fSVPs, we identified in addition to known chaperones such as HSP90AB1 and HSC70, several apolipoprotein-related factors. RNAi-based phenotypic validation identified strongest effects for ApoC1, likely due to two complementary effects. First, ApoC1 depletion reduced intracellular cholesterol level impairing HBV infection and SVP production, which was compensated by exogenous cholesterol substitution. Second, ApoC1 that is mainly enriched in high-density lipoprotein (HDL), associates with HBV virions and fSVPs and increases HBV infectivity. The same was found for hepatitis D virus (HDV), a satellite virus utilizing HBV envelopes. Supplementation of exogenous HDL enhanced infection most likely via scavenger receptor class B type 1 (SR-B1), the natural HDL receptor. Consistently, inhibition of SR-B1 suppressed HBV and HDV infection. ConclusionsWe established a method for obtaining highly purified HBV virions and fSVPs and identified the HDL component ApoC1 to associate with both particle types. ApoC1 promotes HBV and HDV infection most likely via SR-B1 facilitating viral entry.

BackgroundGenetic drift and host-associated adaptation in influenza A viruses threaten the long-term reliability of RT-qPCR-based diagnostics, particularly when nucleotide mismatches arise within primer and probe binding regions. Conventional assay evaluations often emphasize sequence conservation but rarely assess functional mismatch tolerance across divergent subtypes and hosts. MethodsWe performed an in silico evaluation of a matrix (M) gene-targeted RT-qPCR assay by aligning primer and probe binding regions against 22 H1N1 isolates and representative H3N2 and H5N1 reference strains, including recent zoonotic isolates from avian and bovine hosts. Nucleotide mismatches were identified, quantified, and mapped relative to assay components and oligonucleotide termini. Mismatch burden was summarized by subtype and assay region. ResultsH1N1 isolates exhibited complete conservation across primer and probe regions. In contrast, H3N2 and H5N1 strains demonstrated subtype-specific sequence variability, with a total of eleven mismatches identified across seven non-H1N1 isolates (mean mismatch per isolate = 2.43). Probe mismatches predominated (63.6%), occurring primarily at internal positions, while primer mismatches were infrequent and largely avoided 3' terminal nucleotides. Recent H5N1 isolates (2023-2024) shared conserved internal mismatches in the probe and forward primer, whereas a historical H5N1 isolate (2016) exhibited a distinct profile including a terminal probe mismatch. Despite this variability, mismatch patterns were consistent with preserved amplification potential. ConclusionThis study demonstrates that the evaluated influenza A M gene RT-qPCR assay exhibits inherent mismatch tolerance across human and zoonotic subtypes. By shifting diagnostic evaluation from strict sequence identity to functional resilience, our findings provide a framework for designing and maintaining robust molecular assays suitable for surveillance and pandemic preparedness amid ongoing viral evolution. Graphical AbstractIn silico evaluation of an influenza A matrix gene RT-qPCR assay demonstrates subtype-specific primer and probe mismatches across H3N2 and H5N1 strains, including recent zoonotic isolates. Despite observed variability, mismatches predominantly occur at internal positions and spare primer 3' termini, supporting inherent assay mismatch tolerance and suitability for surveillance applications. O_FIG O_LINKSMALLFIG WIDTH=150 HEIGHT=200 SRC="FIGDIR/small/707407v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@e48677org.highwire.dtl.DTLVardef@1380ddcorg.highwire.dtl.DTLVardef@11606f0org.highwire.dtl.DTLVardef@121b4ab_HPS_FORMAT_FIGEXP M_FIG C_FIG

IntroductionGenomic testing is reshaping nephrology practice, yet the structure, outcomes, and implementation of kidney genetics services remain poorly characterized. MethodsWe conducted a two-part scoping study comprising (i) a literature review (JBI methodology, PRISMA-ScR compliant; OSF registration doi.org/10.17605/OSF.IO/N32VA) of English-language publications (2000-2025) describing kidney genetics services and outcomes, and (ii) an international stakeholder consultation of clinic leads to capture real-world service and implementation experiences. ResultsSixty studies were included, predominantly from North America (n=23), followed by United Kingdom/Ireland (n=5), Europe (n=17), Australia/New Zealand (n=10), and Asia (n=5). Among the 25 studies describing clinic models, four types were identified: multidisciplinary integrated (n=12), nephrologist-led (n=9), mainstreaming (n=2), and traditional genetics referral (n=2). Clinic structure varied by region. Outcome reporting focused on diagnostic yield (92%), with limited data on timeliness (16%), patient-reported outcomes (12%), or implementation outcomes (4%). Test penetration was high across regions and models, while diagnostic yield varied. Nephrologist-led clinics demonstrated comparable performance to multidisciplinary models when adequately supported. International stakeholder consultation data (n=48) revealed diversification of clinic models across regions. In Australia/New Zealand, multidisciplinary clinics predominated, supported by public funding and in-house or hybrid laboratory. United Kingdom/Ireland clinics used public funding and a national laboratory. North American clinics show greater heterogeneity, with higher prevalence of nephrologist-led models, reliance on commercial laboratories, and mixed or private funding. Asian clinics reported nephrologist-led models, with resource constraints, and hybrid testing and funding arrangements. Comprehensive sequencing with virtual panels predominated in Australia/New Zealand, United Kingdom, and Europe; phenotype-driven panels {+/-} reflex testing were more common in North America. ConclusionsKidney genetics care is expanding but remains unevenly implemented. Nephrologist-led and multidisciplinary models can be effective with appropriate support. Patient selection may influence diagnostic yield more than testing modality. Standardized outcome reporting and theory-driven implementation evaluation are essential for delivering equitable, sustainable genomic services. Lay SummaryThis study examined how kidney genetics services are delivered across the globe. We reviewed 60 studies (2000-2025) and consulted 48 clinic leaders globally. Four service models were identified--multidisciplinary integrated, nephrologist-led, mainstreaming, and traditional genetics referral--and mapped variation in care teams, test strategies, test laboratories, and funding. Most studies reported diagnostic yield, but few assessed patient experience or how well services were implemented. European programs showed the highest performance, attributed to clear referral criteria, deep phenotyping, detailed family histories, multidisciplinary review, and strong public funding. Clinics led by nephrologists performed comparably to multidisciplinary teams when adequately supported. Across all settings, patient selection was more important than the specific type of genetic test used in determining diagnostic success. Kidney genetics services are expanding but remain uneven. This study highlights the need for context-specific, theory-informed, and determinants-targeted strategies to support scalable, equitable, and sustainable genomic care worldwide.

IntroductionAccess to Hepatitis C virus (HCV) testing and treatment remains low globally. HCV self-testing (HCVST) may facilitate diagnosis and cure. We analysed treatment uptake and outcomes following a positive HCVST result in three distinct African epidemic contexts. MethodsA multi-country cohort study nested within HCVST implementation programmes in Cameroon, Nigeria, and South Africa (May 2023-May 2024). Adults ([&ge;]18 years) with positive HCVST results were followed through confirmatory testing and care outcomes until last event. Co-primary outcomes were: (i) cascade progression, (treatment initiation and sustained virological response [SVR]); estimated using country-cascades; and (ii) cumulative incidence of disengagement from care, estimated using Bayesian competing-risks survival models. Analyses were conducted separately for South Africa and jointly for Cameroon-Nigeria due to structural differences in service organisation. Covariate associations were estimated as hazard ratios. Disease severity was assessed through fibrosis staging derived from AST-to-platelet ratio index (APRI). Results1,341 participants had positive HCVST results (117 in Cameroon, 226 in Nigeria, 998 in South Africa). Among laboratory confirmed HCV cases, treatment initiation and SVR were highest in Cameroon (Tx 98.6%, 71/72; SVR 96.4%, 53/55), followed by Nigeria (Tx 90.8%, 168/185; SVR 91.8%, 56/62), and low in South Africa (Tx 4.3%, 37/854; SVR 60.6%, 3/5). Crude disengagement was lowest in Nigeria (24.4%; 95% CrI 19.1%-30.3%), followed by Cameroon (52.4%; 95% CrI 44.4%-61.2%), and South Africa (77.9%; 95% CrI 76.2%-79.8%). By 24-weeks, disengagement was lower in specialist hospitals than community sites in Cameroon and Nigeria. In South Africa, the greatest predictor of disengagement was HIV positive status (HR 1.96; 95% CrI 1.71 to 2.23). Viraemia exceeded regional estimates (82.2%, 1102/1341), with liver scarring highest in Cameroon (fibrosis: 8.3%, cirrhosis: 6.9%) and lowest in South Africa (2.9% and 1.6%, respectively). ConclusionHCV self-testing enabled detection of HCV cases, including severe disease, but poorer progression in community settings suggests decentralised treatment pathways require strengthening to realise cure.